jiayuasu commented on code in PR #1229:
URL: https://github.com/apache/sedona-db/pull/1229#discussion_r3931183966
##########
python/sedonadb/python/sedonadb/expr/literal.py:
##########
@@ -191,15 +199,137 @@ def _lit_from_shapely(obj):
return _lit_from_wkb_and_crs(obj.wkb, None)
-def _lit_from_wkb_and_crs(wkb, crs):
+def _lit_from_wkb_and_crs(wkb, crs, edge_type=None):
Review Comment:
Done, it's `_lit_from_wkb` now (named for what it builds from rather than
its argument list, since the edge type joined the CRS).
##########
python/sedonadb/python/sedonadb/expr/literal.py:
##########
@@ -191,15 +199,137 @@ def _lit_from_shapely(obj):
return _lit_from_wkb_and_crs(obj.wkb, None)
-def _lit_from_wkb_and_crs(wkb, crs):
+def _lit_from_wkb_and_crs(wkb, crs, edge_type=None):
import geoarrow.pyarrow as ga
import pyarrow as pa
type = ga.wkb().with_crs(crs)
+ if edge_type is not None:
+ type = type.with_edge_type(edge_type)
storage = pa.array([wkb], type.storage_type)
return type.wrap_array(storage)
+def _lit_from_missing(obj):
+ # pandas.NA and numpy.ma.masked both mean "no value".
+ import pyarrow as pa
+
+ return pa.array([None])
+
+
+def _lit_from_nat(obj):
+ # NaT is a datetime missing value in pandas (assigning it yields a
+ # datetime64 column), so it resolves to a typed timestamp null rather
+ # than an untyped NULL.
+ import pyarrow as pa
+
+ return pa.array([None], pa.timestamp("ns"))
Review Comment:
Right on both counts. `NaT` itself carries no unit (it's a unit-less
singleton), so some unit has to be picked, and nanoseconds is where pandas
stores it and the finest one, so it can never be a lossy choice. And it does
coerce: `coalesce(us_col, lit(pd.NaT))` resolves to `timestamp(µs)` and
`coalesce(s_tz_col, lit(pd.NaT))` to `timestamp(s, UTC)`, so the null takes the
surrounding expression's unit and zone. Added that as a comment on the function.
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